Angela Serra

The paper presents an AI workflow for mapping Key Events to genes in Adverse Outcome Pathways, improving accuracy and reducing manual effort through semantic retrieval, LLM refinement, and expert curation.

MUUMI integrates multi-omics data using statistical meta-analysis and network-based methods to identify robust molecular signatures and interactomes.

OpTiles dynamically defines tiling windows for methylation data based on CpG distribution and variability, improving reliability and annotation of targeted methylation datasets.

This paper curates and harmonizes transcriptomics datasets from interstitial lung disease patients to improve data FAIRness and enable integrated systems biology approaches.

This study shows that endothelial cells are sensitive to systemic pro-fibrotic signals and initiate early pro-fibrotic mechanisms in pulmonary fibrosis, independent of other cell types.

This study uses RNA sequencing to analyze immune gene responses in macrophages exposed to bleomycin, identifying dose-dependent gene alterations and linking them to cytokine and proteinase activity.

This study investigates how polarizing environments affect macrophage gene expression and DNA methylation, revealing long-term regulatory responses and common epigenetic changes across stimuli.

This paper develops a network-based toxicology approach to model nanomaterial hazard by linking molecular changes to adverse outcomes in biological systems.

This paper maps disease relationships using six data dimensions to reveal novel insights beyond traditional classifications, identifying shared features between Type 2 diabetes and Alzheimer's disease.

eUTOPIA provides an intuitive R Shiny application for preprocessing and analyzing microarray data without requiring computational expertise.

This paper integrates multi-parametric and multi-regional MRI histogram features to identify patient subgroups with distinct survival outcomes in glioblastoma.